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As 5G and Internet-of-Things (IoT) are deeply integrated into verticalindustries such as autonomous driving and industrial robotics, timely statusupdate is crucial for remote monitoring and control. In this regard, Age ofInformation (AoI) has been proposed to measure the freshness of status updates.However, it is just a metric changing linearly with time and irrelevant ofcontext-awareness. We propose a context-based metric, named as Urgency ofInformation (UoI), to measure the nonlinear time-varying importance and thenon-uniform context-dependence of the status information. This paper firstestablishes a theoretical framework for UoI characterization and then providesUoI-optimal status updating and user scheduling schemes in both single-terminaland multi-terminal cases. Specifically, an update-index-based scheme isproposed for a single-terminal system, where the terminal always updates andtransmits when its update index is larger than a threshold. For themulti-terminal case, the UoI of the proposed scheduling scheme is proven to beupper-bounded and its decentralized implementation by Carrier Sensing MultipleAccess with Collision Avoidance (CSMA/CA) is also provided. In the simulations,the proposed updating and scheduling schemes notably outperform the existingones such as round robin and AoI-optimal schemes in terms of UoI, error-boundviolation and control system stability.

Urgency of Information for Context-Aware Timely Status Updates in Remote Control Systems